Improving schema understandability for semantic integration

提高语义集成的模式可理解性

• 批准号: 312129-2011
• 负责人: Pottinger, Rachel
• 金额: $ 1.75万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=571696
• 关键词: Improving; schema; understandability; semantic; integration

Databases are very complex; a typical database can store data in hundreds of tables and can contain hundreds of references between tables. The layout of the data into tables and references between them is referred to as a schema. Learning the details of these complex schemas requires significant time. This problem is exacerbated by data sources being shared across organizations, and users attempting to make their applications do something for which they were not originally designed. Consider the following two scenarios: (1) A user is integrating civil engineering data across a number of applications, including CAD models and project scheduling. The data in these applications can be exported via a number of different standards. In order to integrate the data, the user must first choose which standard to export from and then figure out how to understand how the data has been exported. (2) An end user has access to a database application that generates reports. The end user asks the database programmer to change the application to access more information than was originally accessible. The programmer has never seen the application before, but now must extend the application to access new data. This will require the programmer to understand how the data in the back-end database is stored well enough to write the new queries. Neither of these scenarios is adequately helped by existing approaches. I propose to improve schema understanding. The goal is to help users in a variety of scenarios including those above to make better use of the existing schemas that they are encountering for the first time, whether it is extending their understanding of a current application, trying to decide how to export their data to a standard schema (which is challenging since related data may be scattered across the standard schema, rendering it incomprehensible), or choosing a standard schema to which the data should adhere.

数据库非常复杂；典型的数据库可以将数据存储在数百个表中，并且可以在表之间包含数百个引用。 数据在表中的布局以及它们之间的引用称为模式。 学习这些复杂模式的细节需要大量时间。 由于跨组织共享数据源，以及用户试图让他们的应用程序执行最初设计时没有执行的操作，这个问题变得更加严重。考虑以下两种情况： (1) 用户正在跨多个应用程序集成土木工程数据，包括 CAD 模型和项目调度。 这些应用程序中的数据可以通过多种不同的标准导出。 为了整合数据，用户必须首先选择要导出的标准，然后弄清楚如何了解数据是如何导出的。 (2) 最终用户可以访问生成报告的数据库应用程序。 最终用户要求数据库程序员更改应用程序以访问比最初可访问的更多信息。 程序员以前从未见过该应用程序，但现在必须扩展该应用程序以访问新数据。 这将要求程序员了解后端数据库中的数据如何存储得足够好以编写新查询。 现有方法都无法充分帮助这两种情况。 我建议提高模式理解。目标是帮助包括上述在内的各种场景中的用户更好地利用他们第一次遇到的现有模式，无论是扩展他们对当前应用程序的理解，尝试决定如何将数据导出到标准模式（这是具有挑战性的，因为相关数据可能分散在标准模式中，使其难以理解），或者选择数据应遵循的标准模式。